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Measuring access to public transport in European cities

This study outlines a harmonized approach to measure public transport accessibility in European cities, utilizing detailed location data, service frequencies, and population distribution to determine urban mobility. Challenges and sources are also discussed.

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Measuring access to public transport in European cities

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  1. Measuring access to public transport in European cities Hugo Poelman REGIO-GIS DG Regional and Urban Policy

  2. Measuring access to public transport • Location of all public transport stops • Frequency of services • bus and tram • trains and metros • Population per building block based on • detailed population grids • census tracts • neighbourhood statistics • plus disaggregation using land use data and/or imperviousness if needed

  3. General Transit Feed Specification model

  4. Location of stops Bus and tram Train and metro Stockholm

  5. Average stops an hour from 6 am to 8 pm on a normal week day

  6. Service areas around stops • Stops near to each other are clustered • bothsides of a street; bus stations • sum of availabledepartures per cluster • Service areas • 5 minutes walking distance for bus and tram • 10 minutes for train and metro • using comprehensive street network, accessible to pedestrians

  7. Frequency classes • Number of departures per service area • In overlapping areas: maximum value of the overlapping service areas • Frequency classes • High: > 10 departures an hour • Medium: more than 4 but less than 10 an hour • Low: less than 4 an hour • Null: no public transport stops withinwalking distance

  8. Combined frequency classes

  9. Population distribution Urban Atlas Population by block

  10. Four spatial levels: City, Urban Centre, Greater City and Larger Urban Zone Larger Urban Zone is not shown on these samples: It includes the area with substantial commuting to the city.

  11. Stockholm: areas and population by access to public transport and its frequency 844,000 1,135,000 1,542,000 2,042,000 inh. inh. inh. inh.

  12. Population distribution and number of departures in large cities* Y% of population has access to at least X departures an hour * cities: defined as urban centres

  13. Population distribution and number of departures in mid-size cities* Y% of population has access to at least X departures an hour * cities: defined as urban centres

  14. Conclusion • A new harmonised way of assessing access to public transport • Gives an internationally comparable method of assessment • Can also be used to develop regional indicators • Uses big data: millions of departures, thousands of bus, tram, train and metro stops

  15. Challenges • Timeliness and spatial resolution of population distribution data • Harmonised implementation of public transport data standards • Understanding and conversion of data according to national standards • Differences in open data policy implementation, data licensing policy • Theoretical versus real-life transport offer

  16. Sources • Delineation of cities: EC-OECD city definitions • Population distribution: NSIs, GEOSTAT 2006 grid • Copernicus Urban Atlas 2006 land use data • Road network: TomTom MultiNet • Public transport data: BE: VVM De Lijn, STIB-MIVB, SRWT-TEC, Infrabel; DK: Rejseplanen.dk; IE: dublinked.ie, LUAS, Irish Rail; EE: www.peatus.ee; FR: open data portals of cities/départements; NL: OV-9292; FI: www.matka.fi, HSL; SE: www.trafiklab.se; UK: Data.gov.uk (NapTAN and NPTDR); various cities: http://www.gtfs-data-exchange.com/agencies; Die Bahn

  17. Questions ?

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